Gaia unifies design, operation, and governance for enterprise AI.
An end-to-end platform for designing, running, and governing enterprise AI agents — built in-house or sourced externally.
The end-to-end platform for enterprise agentic AI systems.
Gaia complements existing AI implementations by unifying design, execution, and evolution in one system.
- Compose agents, models, data, and tools in one governed system.
- Turn design-time intent into runtime enforcement with policies and constraints.
- Share operational capabilities across teams, clouds, and providers.
Code-first frameworks
Maximum flexibility, but heavy engineering and integration overhead.
- • Governance rebuilt per system
- • Breaks down beyond a single team
Copilot / no-code tools
Fast initial results, but limited system depth.
- • Constrained extensibility
- • Operational gaps at scale
Gaia closes the gap between intent and operation.
Design-time intent drives runtime actions and guardrails automatically.
Agents, tools, and models operate as one orchestrated whole.
Evaluation signals and audit trails guide safe evolution over time.
The three pillars
Governance, collaboration, and velocity — embedded by design.
GLASSBOX
Policies, constraints, and auditability are embedded in how the system runs.
CO-DEVELOPMENT
Business, UX, and engineering collaborate in real time with the same system view.
PRODUCTIVITY & VELOCITY
Speed increases over time without sacrificing governance or quality.
What Gaia controls
Shared lifecycle capabilities across design, execution, and evolution.
Agent orchestration
Coordinate multiple agents with policy-aware routing and execution.
Model & tool execution
Run multi-model workflows with reliable tool control and observability.
Data & context access
Governed access to enterprise knowledge and contextual data.
User interaction layers
Deliver experiences through web, API, and multimodal interfaces.
Evaluation & quality management
Continuous evaluation signals keep systems safe and performant.
Auditability & access control
Traceable actions, role-based access, and lifecycle governance.
Gaia operates as a complete platform.
Execution, knowledge, and governance layers work together so AI systems behave as long-lived operational assets.
Delivery lifecycle built into the platform
Governed artifacts
Capture intent, policy, and constraints as first-class system assets.
Policy-aware execution
Runtime tool usage respects governance and structural primitives.
Continuous evaluation signals
Quality, safety, and performance are measured continuously.
Managed system evolution
Operate, audit, and evolve AI systems with confidence.
Multi-cloud observability, multi-model freedom.
Centralize logs from Azure, Google Cloud, AWS, and Oracle (OCI) while orchestrating OpenAI, Claude, Gemini, Mistral, and any model from any vendor.
Microsoft Azure
Google Cloud
Amazon AWS
Oracle OCI
OpenAI
Claude
Gemini
MistralFor teams operating AI as core infrastructure.
Gaia is designed for enterprises that need stability, governance, and long-term evolution of AI systems.
- Teams building long-lived AI systems instead of one-off assistants.
- Organizations operating in regulated or risk-sensitive environments.
- Enterprises scaling from pilots to managed AI portfolios.
Governed artifacts
Design-time intent becomes runtime rules.
Policy-aware tool usage
Tools execute within defined policy boundaries.
Continuous evaluation
Quality signals drive evolution.
Operate AI systems as enterprise infrastructure.
Gaia delivers governance, collaboration, and velocity across the full lifecycle of agentic AI.